Managing modulation transfer function values for image data

Abstract

An image scanner is provided with a super-resolution processing function for generating a high-resolution image using multiple pieces of low-resolution image data. The scanner device then measures an initial MTF value without performing the super-resolution processing, refers to an MTF properties table in which is registered a number of pieces of low-resolution image data for a scanner device of that type to achieve a pre-set target MTF, and registers the number of images that corresponds to the initial MTF value in the scanner, if that number is present, and registers an interpolated value if that number is not present. The image scanner then performs the super-resolution processing using the registered number of pieces of low-resolution image data, and outputs image data of a target resolution.

Description

BACKGROUND OF THE INVENTION[0001]1. Field of the Invention[0002]The present invention relates to an image processing apparatus, image processing method, information processing apparatus, and information processing method, that use, for example, super-resolution techniques.[0003]2. Description of the Related Art[0004]Digital copiers, which read an image of a document using a scanner and make copies using the obtained image data, and image processing systems, which analyze image data and convert that image data into document data, are available as of late. Due to variance in the properties, optical processing, and so on of the scanning elements, scanners that use image sensors such as CCDs, CISs, and so on sometimes experience differences in scanning resolutions, or in other words, differences in Modulation Transfer Functions (MTFs) at the individual scanner unit level.[0005]When the MTF is low, image objects that should have high resolution, such as small characters and the like, exp...

AI Technical Summary

Benefits of technology

[0012]The present invention has been conceived in light of the abovementioned related art. Specifically, first, the present invention resolves individual differences in the MTFs of scanners using super-resolution processing. Second, the present invention provides an image processing apparatus capable of obtaining an optimal image regardless of individual characteristics by resolving the individual differences in MTFs using super-resolution processing. Third, the present invention provides an image processing apparatus that makes MTFs constant between apparatuses when multiple image reading apparatuses are installed, thereby suppressing variance in the reading results, and ensuring that the MTF is constant regardless of which image reading apparatus performed the reading. Finally, fourth, the present invention provides an image processing apparatus that has a stable MTF by suppressing changes in the MTF due to deterioration over time.

[0016]According to the present invention, the MTF of scanned image data can be kept constant regardless of individual differences, model differences, and so on of scanners. This prevents a drop in yield caused by variance in the resolutions in scanner products, and makes it possible to correct changes in resolution caused by deterioration over time.

Problems solved by technology

When the MTF is low, image objects that should have high resolution, such as small characters and the like, experience a drop in image quality, resulting in the characters scanned by the scanner being unreadable, distorted, and so on.

For this reason, there are cases where optical character recognition (OCR) carried out on the scanned data cannot successfully extract the characters.

MTF correction using conventional MTF filters, as described above, does not actually increase the resolution of the image data itself, and is thus limited in how much it can improve resolution.

There is also a problem with systems that use multiple scanners in that the results of processing read image data may differ due to variances in the MTFs at the scanner level.

For example, there are cases where the results obtained by running an OCR process on a certain document image using a certain multifunction peripheral device (MFP) do not match the results obtained by running an OCR process on the same document image using a different MFP of the same type.

Furthermore, there is a problem in that the MTF of a scanner will drop due to deterioration in the light source, image sensor elements, and so on occurring over time as the scanner unit is used.

There is therefore a problem in that, for example, characters that were once recognizable when a certain MFP was new become unreadable as time passes, leading to an increase in recognition errors and so on.

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